Software Defined Networking (SDN) and/or control planes offer an opportunity to improve current network management practices with automated optimization processes. This is in contrast with current practices where managing a network is performed by a human. With the increased complexity of networks and availability of computers for big data analysis of network measurements, it is expected that many of the tasks performed by humans may now be performed by computerized systems in a more optimal fashion. With respect to operating a network, understanding the bandwidth usage is critical for traffic management (admission control and bandwidth pricing) and for network planning (future capacity). With the complexity of modern networks, there is a need to analyze and summarize network measurements into a useful statistical representation of network traffic or network status, and then incorporate these statistics into network management or business decisions. This is a so-called bandwidth representation or representative bandwidth. Conventional approaches for bandwidth representation use a scaling factor (overbooking factor) to approximate the actual traffic from requested traffic. Scaling is determined manually by a network operator. This approach has limitations in that it does not provide sufficient information to produce optimal inputs to management algorithms; generally speaking, in today's network it is also used network-wide and is therefore a sub-optimal, one-size-fits all approach. Also, conventional approaches use parametric (Poissonian) telephony traffic approaches to approximate connection level bandwidth requests, which are not optimized for modern packet bandwidth requests, which generally do not have Poissonian characteristics.